期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：7
页码：299-308
DOI：10.14257/ijsip.2015.8.7.29
出版社：SERSC
摘要：Action tracking and recognition is a challenge due to human deformation and complex scene system. Tracking-by-detection methods are used to solve appearance changes problem caused by viewpoint, occlusion, scale or deformation. Here we propose a robust object tracking and generative action recognition method. Compressive sensing is improved to track object with superpixels, and the generative structural part model is designed to be adaptive to variation of deformable object. We evaluate the method on challenging sequences. Also, we make qualitative and quantitative discussion. The results indicate the method is robust, and it is adaptive to deformable object tracking and action recognition
关键词：object tracking; action recognition; compressive sensing; generative part ; model
